Communities DATA-SCIENCE-OPTIMIZE Practice Questions (Page 2)

Questions 6–10

1. 6foundation · easy

   Which community detection algorithm is known for its hierarchical approach that repeatedly removes edges with the highest betweenness centrality to reveal community structure?

   • AGirvan-Newman
   • BLabel Propagation
   • CLouvain
   • DClique Percolation
   Reveal Solution Discussion Select an answer first
2. 7expert · hard

   A researcher is analyzing a biological network where nodes are genes and edges indicate co-expression. The researcher expects that some genes are involved in multiple biological processes and wants to detect overlapping communities. The researcher also wants to control the size of the communities. Which parameter in clique percolation should be adjusted?

   • AThe conductance threshold
   • BThe k value (clique size)
   • CThe modularity threshold
   • DThe number of iterations
   Reveal Solution Discussion Select an answer first
4. 8expert · hard

   A network analyst is comparing two community detection algorithms on the same network. Algorithm A produces a partition with modularity 0.50, while Algorithm B produces a partition with modularity 0.45. However, Algorithm A's partition has a much lower conductance for some communities. The analyst needs to choose a partition for a fraud detection system that relies on identifying tightly-knit groups. Which partition should be chosen?

   • AAlgorithm A, because it has higher modularity and lower conductance.
   • BAlgorithm A, because higher modularity is always better.
   • CAlgorithm B, because it has higher modularity.
   • DAlgorithm B, because lower conductance indicates better community separation.
   Reveal Solution Discussion Select an answer first
5. 9foundation · easy

   Which community evaluation metric is defined as the ratio of the number of edges leaving the community to the total degree of the nodes in the community?

   • ACoverage
   • BConductance
   • CClustering coefficient
   • DModularity
   Reveal Solution Discussion Select an answer first
6. 10application · medium

   A social media analyst is studying a large user interaction network with millions of nodes and edges. The goal is to identify communities quickly for a real-time recommendation system. The analyst needs an algorithm that scales well and does not require pre-specifying the number of communities. Which algorithm should the analyst choose?

   • AGirvan-Newman
   • BK-means clustering
   • CClique percolation
   • DLouvain
   Reveal Solution Discussion Select an answer first